Factors Impacting Loan Defaults: The Case of Thai SME Loans in Bangkok Metropolitan Region
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Abstract
This paper aims to investigate factors impacting on bank loan defaults of Thai SME enterprises in Bangkok and the Bangkok Metropolitan Region. The authors focus on enterprises who are normal debtors, and have credit limit for business in
the types of long-term loan and overdraft. We obtain data on Thai SMEs including enterprise’s characteristics, financial performance, credit information, types of loans, types of industry and loan default information. The samples in this study are totally 592 enterprises, covering the period of 2013 to 2015. We apply a logit model with control variables such as loan types, industries and bank loan regions. Using panel logit regression, our results show that about 17% of the entire sample has bank loan defaults. We find that SMEs default on long-term loans at a higher rate than SMEs with overdraft (OD). Additionally, size of bank loan (credit limit) and enterprise’s age are negatively related to the likelihood of bank loan defaults.
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Research Articles
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References
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Yamane, T. (1973). Statistics: An introductory analysis. 3nd ed. New York: Harper and Row Publication.
Zmijewski, M. E. (1984). Methodological issues related to the estimation of financial distress prediction models. Journal of Accounting Research. 22(1): 59-82.
Alibaba Group. (2018). History and milestones [On-line]. Available: https://www.alibabagroup.com/en/about/history?year=2014
Amnuayprawit, S. (2016). The strategic access to the capital for small and medium enterprises in Bangkok. (In Thai). Ph.D. Dissertation, Kasem Bundit University, Thailand.
Asantey, O. J., and Tengey, S. (2014). The determinants of bad loans in finance small and medium Enterprises in the banking sector in Ghana: A factorial analysis. Ghana: Standard Chartered Bank Ghana.
Ayyagari, M., Demirguc, A-K., and Maksimovic, V. (2011). Small vs. Young Firms across the world – Contribution to Employment, Job Creation, and Growth. n.p.; cited in Edinburgh Group. (2012). SMEs: The big picture. Growing the global economy through SMEs. 2012(1): 6-20.
Bangkok Bank. (2017). Branches. (In Thai). Annual report 2017. 2017(1): 204-224.
Bank of Thailand (BOT), Relationship Communication Office, Organization Communication Department. (2017). Performance of commercial bank system in 2016. (In Thai). News by BOT 2017. 2017(1): 1-2.
_____. Academic section of northeastern office. (1997). Access to capital sources of SMEs: The case of northeastern of Thailand. (In Thai). Bangkok: Bank of Thailand (BOT).
Brown, K., and Moles, P. (2016). Credit Risk Management. 2nd ed. Edinburgh: Heriot-Watt University.
Bunbanyen, C. (2004). Models of probabilistic measurement of non-performing loans (NPLs) in Thailand. (In Thai.). M.S. thesis, Kasetsart University, Thailand.
Edinburgh Group. (2012). SMEs: The big picture. Growing the global economy through SMEs. 2012(1): 6-20.
Gattni, L., and Sojan, D. (Eds.). (2016). Demand for finance. Assessment of financing needs of SMEs in the Western Balkans countries. 2016(7): 13-21.
Iampoom, J., and Tangwirut, A. (2016). Reviewing on stat in focus by Bank of Thailand (BOT). (In Thai). Stat in Focus. 2016(1): 3-5.
Inupat, A., Naknok, S., and Aiamkong, N. (2016). Credit considering factors affecting non-performing loan of bank for agriculture and agricultural cooperative in Pathum Thani province. (In Thai.). M.S thesis, Valaya Alongkorn Rajabhat University under the Royal Patronage, Thailand.
Kanchanawasee, S. (2012). Applied statistics for behavior research. (In Thai). 6th ed. Bangkok: Chulalongkorn University Press.
Klongphol, B. (2004). Factors determining the probability of debt default: The case of real estate and construction sectors listed on the Stock Exchange of Thailand (SET). (In Thai). M.S thesis, Dhurakij Pundit University, Thailand.
Kofi, A-S. E., and Portia, B. (2015). Determinants of Business Loan Default in Ghana. Junior Scientific Researcher. 1(1): 10-26.
Meknuea, C. (2012). Measures of importance in the selection of research statistics. [On-line]. Available: https://www.gotoknow.org/posts/431764
Mccann, F., and Calder, T. M. (2012). Determinants of SME Loan Default: The Importance of Borrower-Level Heterogeneity. Ireland: Central Bank of Ireland.
Muangpean, P. (2012). Credit risk management for increasing efficiency of the Government Savings Banks in Bangkok and metropolitan area. M.S thesis, Rajamangala University of Technology Thanyaburi, Thailand.
Murray, R. F. (1959). Evaluating Credit Worthiness. Business Loans of American Commercial Banks, (n.p.).
Novabizz. (2015). Types of Credits and Sources of Credit. [On-line]. Available: http://www.novabizz.net/credit-2.html
Office of Small and Medium Enterprise Promotion (OSMEP). (2015). Report a situation small and medium (SME) enterprises in 2014. (In Thai). n.p.; cited in Iampoom, J. and Tangwirut, A. (2016). Reviewing on stat in focus by Bank of Thailand (BOT). (In Thai). Stat in Focus. 2016(1): 1-2.
Phuchpanphol, W. (2005). Credit management of financial institution. (In Thai). 6th ed. Bangkok: Auksornshopol.
Rangsoongnuen, K. (2011). Factor analysis with SPSS and AMOS for research. (In Thai). Bangkok: SE-ED book publisher.
Sakaranan, S., Banthat, W., Chiwamitr, S., and Phuddhawiboon, D. (1987). Credit Management. (In Thai). Bangkok: Sukhothai Thammathirat Open University.
Wattana, S. (2015). National agenda of the opportunity on accelerating SMEs growth in National Council for Peace and Order (NCPO)’s era [On-line]. (In Thai). Available: https://www.bot.or.th/Thai/MonetaryPolicy/NorthEastern/DocLib_Research/02-SMEs_Full.pdf
World Bank. (2015). Small and medium enterprises (SMEs) finance: Improving SMEs’ access to finance and finding innovative solutions to unlock sources of capital [On-line]. Available: http://www.worldbank.org/en/topic/smefinance
Yamane, T. (1973). Statistics: An introductory analysis. 3nd ed. New York: Harper and Row Publication.
Zmijewski, M. E. (1984). Methodological issues related to the estimation of financial distress prediction models. Journal of Accounting Research. 22(1): 59-82.